Online Signature Verification System Based on Support Vector Data Description
Wu Zhong · 2011
An online signature verification system is proposed based on support vector data description (SVDD).Firstly,correspondences of the critical points in signatures are confirmed by bidirectional backward-merging dynamic time wrapping algorithm.Then,subtle differences in the local are calculated by classical dynamic time wrapping algorithm.Feature selection principle based on mean and deviation minimization is proposed.Finally,the classifiers are designed using SVDD.To obtain better result,m-fold cross validation and genetic algorithm are used to seek optimal parameters of SVDD.The average equal error rate for skill forge signatures on SVC2004 signatures database is 4.25%.